Allows running a meta-analysis of multivariate Genome Wide
Association Studies (GWAS) and easily visualizing results through custom
plotting functions. The multivariate setting implies that results for each
single nucleotide polymorphism (SNP) include several effect sizes (also
known as "beta coefficients", one for each trait), as well as related
variance values, but also covariance between the betas. The main goal of
the package is to provide combined beta coefficients across different
cohorts, together with the combined variance/covariance matrix. The method
is inverse-variance based, thus each beta is weighted by the inverse of its
variance-covariance matrix, before taking the average across all betas. The
default options of the main function \code{multi_meta} will work with files
obtained from GEMMA multivariate option for GWAS (Zhou & Stephens, 2014).
It will work with any other output, as soon as columns are formatted to
have the according names. The package also provides several plotting
functions for QQ-plots, Manhattan Plots and custom summary plots.